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A complete implementation of a Decoder-Only Transformer (GPT-style) built using PyTorch, without relying on high-level abstractions. This implementation includes all core components: token embeddings, positional embeddings, multi-head self-attention, feedforward networks, causal masking, and output logits generation.
A complete implementation of the "Attention Is All You Need" Transformer model from scratch using PyTorch. This project focuses on building and training a Transformer for neural machine translation (English-to-Italian) on the OpusBooks dataset.